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<title>Minim : : FFT : : specSize</title>
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    	<span class="indexheader">Minim</span><br/>
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    	<p class="mainTextName"><A href="fouriertransform_class_fouriertransform.html">FourierTransform</A></p>
    	<p class="methodName">specSize</p>
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    	<p class="memberSectionHeader">Description</p>
    	Returns the size of the spectrum created by this transform. In other words,
 the number of frequency bands produced by this transform. This is typically
 equal to <code>timeSize()/2 + 1</code>, see above for an explanation.
    	
    	<p class="memberSectionHeader">Signature</p>
    	<pre>int specSize()
</pre>
    	
    	
    	
   <p class="memberSectionHeader">Returns</p> 
   <p>int: the size of the spectrum</p>
   
    	
    	<p class="memberSectionHeader">Related</p>
    	<A href="fft_class_fft.html">FFT</A><BR>

    	
    	<p class="memberSectionHeader">Example</p>
    	<pre>/**
  * This sketch demonstrates how to use an FFT to analyze
  * the audio being generated by an AudioPlayer.
  * &lt;p>
  * FFT stands for Fast Fourier Transform, which is a 
  * method of analyzing audio that allows you to visualize 
  * the frequency content of a signal. You've seen 
  * visualizations like this before in music players 
  * and car stereos.
  * &lt;p>
  * For more information about Minim and additional features, 
  * visit http://code.compartmental.net/minim/
  */

import ddf.minim.analysis.*;
import ddf.minim.*;

Minim       minim;
AudioPlayer jingle;
FFT         fft;

void setup()
{
  size(512, 200, P3D);
  
  minim = new Minim(this);
  
  // specify that we want the audio buffers of the AudioPlayer
  // to be 1024 samples long because our FFT needs to have 
  // a power-of-two buffer size and this is a good size.
  jingle = minim.loadFile("jingle.mp3", 1024);
  
  // loop the file indefinitely
  jingle.loop();
  
  // create an FFT object that has a time-domain buffer 
  // the same size as jingle's sample buffer
  // note that this needs to be a power of two 
  // and that it means the size of the spectrum will be half as large.
  fft = new FFT( jingle.bufferSize(), jingle.sampleRate() );
  
}

void draw()
{
  background(0);
  stroke(255);
  
  // perform a forward FFT on the samples in jingle's mix buffer,
  // which contains the mix of both the left and right channels of the file
  fft.forward( jingle.mix );
  
  for(int i = 0; i &lt; fft.specSize(); i++)
  {
    // draw the line for frequency band i, scaling it up a bit so we can see it
    line( i, height, i, height - fft.getBand(i)*8 );
  }
}
</pre>
    	
    	<p class="memberSectionHeader">Usage</p>
    	Web & Application
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